An inverse identification strategy for the mechanical parameters of a phenomenological hysteretic constitutive model
•We present an algorithm for the identification of experimental hysteresis loops.•The algorithm uses a previously investigated and very versatile constitutive model.•It proved to be robust, stable and accurate in analyzing four experimental loops. An inverse strategy is developed for identifying the...
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Published in: | Mechanical systems and signal processing Vol. 139; p. 106622 |
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Abstract | •We present an algorithm for the identification of experimental hysteresis loops.•The algorithm uses a previously investigated and very versatile constitutive model.•It proved to be robust, stable and accurate in analyzing four experimental loops.
An inverse strategy is developed for identifying the parameters of the hysteretic phenomenological constitutive model presented in Vaiana et al. (2019) and belonging to a wider class of hysteretic models. The model, differently from the celebrated Bouc-Wen one, permits the definition of either stress-strain or load-displacement relationships by closed-form expressions that do not require any iterative algorithm for the complete characterization of its response. The identification strategy is based on two optimization procedures performed in sequence in which a mean-square residual between a target and a computed response is minimized. The computation of suitable first trials is shown to represent an essential step of the procedure and is performed by taking advantage of the fact that its parameters correspond to physical quantities characterizing the experimental hysteretic loop. The procedure has been tested by identifying the mechanical parameters of two theoretical and four experimental responses for which numerical results prove the robustness and effectiveness of the proposed identification strategy. |
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AbstractList | •We present an algorithm for the identification of experimental hysteresis loops.•The algorithm uses a previously investigated and very versatile constitutive model.•It proved to be robust, stable and accurate in analyzing four experimental loops.
An inverse strategy is developed for identifying the parameters of the hysteretic phenomenological constitutive model presented in Vaiana et al. (2019) and belonging to a wider class of hysteretic models. The model, differently from the celebrated Bouc-Wen one, permits the definition of either stress-strain or load-displacement relationships by closed-form expressions that do not require any iterative algorithm for the complete characterization of its response. The identification strategy is based on two optimization procedures performed in sequence in which a mean-square residual between a target and a computed response is minimized. The computation of suitable first trials is shown to represent an essential step of the procedure and is performed by taking advantage of the fact that its parameters correspond to physical quantities characterizing the experimental hysteretic loop. The procedure has been tested by identifying the mechanical parameters of two theoretical and four experimental responses for which numerical results prove the robustness and effectiveness of the proposed identification strategy. An inverse strategy is developed for identifying the parameters of the hysteretic phenomenological constitutive model presented in Vaiana et al. (2019) and belonging to a wider class of hysteretic models. The model, differently from the celebrated Bouc-Wen one, permits the definition of either stress-strain or load-displacement relationships by closed-form expressions that do not require any iterative algorithm for the complete characterization of its response. The identification strategy is based on two optimization procedures performed in sequence in which a mean-square residual between a target and a computed response is minimized. The computation of suitable first trials is shown to represent an essential step of the procedure and is performed by taking advantage of the fact that its parameters correspond to physical quantities characterizing the experimental hysteretic loop. The procedure has been tested by identifying the mechanical parameters of two theoretical and four experimental responses for which numerical results prove the robustness and effectiveness of the proposed identification strategy. |
ArticleNumber | 106622 |
Author | Paradiso, Massimo Rosati, Luciano Vaiana, Nicoló Sessa, Salvatore |
Author_xml | – sequence: 1 givenname: Salvatore orcidid: 0000-0003-3209-5051 surname: Sessa fullname: Sessa, Salvatore email: salvatore.sessa2@unina.it organization: Department of Structures for Engineering and Architecture, University of Naples Federico II, Via Claudio, 21, 80124 Napoli, Italy – sequence: 2 givenname: Nicoló surname: Vaiana fullname: Vaiana, Nicoló organization: Department of Structures for Engineering and Architecture, University of Naples Federico II, Via Claudio, 21, 80124 Napoli, Italy – sequence: 3 givenname: Massimo surname: Paradiso fullname: Paradiso, Massimo organization: Department of Structures for Engineering and Architecture, University of Naples Federico II, Via Claudio, 21, 80124 Napoli, Italy – sequence: 4 givenname: Luciano surname: Rosati fullname: Rosati, Luciano organization: Department of Structures for Engineering and Architecture, University of Naples Federico II, Via Claudio, 21, 80124 Napoli, Italy |
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Snippet | •We present an algorithm for the identification of experimental hysteresis loops.•The algorithm uses a previously investigated and very versatile constitutive... An inverse strategy is developed for identifying the parameters of the hysteretic phenomenological constitutive model presented in Vaiana et al. (2019) and... |
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SubjectTerms | Bouc Wen model Constitutive models Hysteresis Hysteretic materials Inverse identification Iterative algorithms Iterative methods Mathematical models Mechanical properties Optimization Parameter identification Robustness (mathematics) Strategy |
Title | An inverse identification strategy for the mechanical parameters of a phenomenological hysteretic constitutive model |
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